You know genomics and you like to share your knowledge. You have broad competence in the field and expert knowledge of some part of it.
You know how to tell good information from bad, how to draw interesting and intellectually responsible results from good information; and how to communicate those results in an accurate and engaging way.
You are ready to refine your knowledge and to keep learning about a quickly changing field.
You understand significance testing in differential expression. You can explain the differences between Cuffdiff and DESeq, both in intuitive terms and more technically. You understand normalization and the issues it raises.
You know enough about the upstream RNA-Seq protocols to be able to interpret their results appropriately. You also know the basic biology of RNA: gene structure, tRNA, homopolymers and poly(A) tails, promoter sites, repressors, cryptic unstable transcripts, isoforms, and so on.
You have worked with large RNA-Seq data sets. You know annotation databases and the related ecosystem of standards and tools. You’re familiar with RefSeq and GENCODE. You are familiar with tools like TopHat, Bowtie, STAR, and BLAT, and you’ve thought carefully about how RNA data presents specific challenges for alignment algorithms.
It would be nice if you also have experience with single-cell transcriptomes and strand-specific data.
You will work with our industry-leading team and data to plan, write, and publish articles and results. You will find the best venues and methods to explain your results to the community. You have academic publications, a good blog, or other experience writing about science.